An Optimization Model for Scheduling Army Base Realignment and Closure Actions

Abstract

The United States Army is reducing and reshaping its force structure to adapt to the nation's changing defense needs and budget constraints. Along with significant personnel reductions, the Army is divesting itself of excess infrastructure through a process of Base Realignment and Closure (BRAC). A necessary step in the BRAC process is calculation of the Net Present Value (NPV) of savings associated with base realignments and closures which must be computed using the Cost of Base Realignment Actions (COBRA) model. COBRA is not an optimization model. The user must enter when specific BRAC actions will occur. This thesis develops a mixed integer linear programming model to assist The Army Basing Study (TABS), the primary analysis agency for Army BRAC issues, schedule slated BRAC actions. The model generates an optimal schedule which attains maximum potential savings within budgetary constraints. In the past, Army analysts have accomplished this scheduling within COBRA using a time consuming process with no guarantee of optimality. Using a systematic time efficient approach, the model achieved a 34% increase in savings ($223 million) over the manual schedule developed by TABS for an actual BRAC 93 scenario.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1994
Accession Number
ADA286141

Entities

People

  • Edward J. Free

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Biomedical
  • C4I
  • Human Systems

DTIC Thesaurus Topics

  • Base Closures
  • Budgets
  • Computer Programming
  • Construction
  • Data Sets
  • Economic Analysis
  • Force Structure
  • Infrastructure
  • Integer Programming
  • Linear Programming
  • Mathematical Programming
  • Military Budgets
  • Military Personnel
  • Operations Research
  • Optimization
  • Scheduling (Production)
  • United States

Readers

  • Environmental Impact Assessment (EIA) of Proposed Air Force Base Actions.
  • Life Cycle Cost Analysis